A metrological spectral difference space for the statistical modelling of hyperspectral images

Hilda Deborah, Noel Richard, Magnus Orn Ulfarsson, Jon Atli Benediktsson, Jon Yngve Hardeberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Answering to metrological constraints typically required in the context of industrial and medical applications, a spectral difference space is introduced in this work. In this space, an acquired hyperspectral data is treated as measurements. Then, modelling the spectral difference space as multivariate Normal laws, a Gaussian mixture model is used in a classification task of remote sensing images. An encouraging result is obtained, comparing the proposed space with a data-driven one. Moreover, it offers a starting point in developing a directly interpretable spectral analysis tools.

Original languageEnglish
Title of host publication2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1104-1107
Number of pages4
ISBN (Electronic)9781538691540
DOIs
Publication statusPublished - Jul 2019
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 28 Jul 20192 Aug 2019

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Country/TerritoryJapan
CityYokohama
Period28/07/192/08/19

Bibliographical note

Publisher Copyright: © 2019 IEEE.

Other keywords

  • Gaussian mixture model
  • hyperspectral imaging
  • image classification
  • metrology

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